# Predloga:Infopolje Verjetnostna porazdelitev Dokumentacija predloge

### Usage

The Template:Infobox probability distribution generates a right-hand side infobox, based on the specified parameters. To use this template, copy the following code in your article and fill in as appropriate:

{{infopolje Verjetnostna porazdelitev
| name       =
| type       =
| pdf_image  =
| cdf_image  =
| notation   =
| parameters =
| support    =
| pdf        =
| cdf        =
| quantile   =
| mean       =
| median     =
| mode       =
| variance   =
| skewness   =
| kurtosis   =
| entropy    =
| mgf        =
| cf         =
| pgf        =
| fisher     =
}}


#### Parameters

• name — Name at the top of the infobox; should be the name of the distribution without the word "distribution" in it, e.g. "Normal", "Exponential" (optional).
• type — possible values are “discrete” (or “mass”), “continuous” (or “density”), and “multivariate”.
• pdf_image — probability density image-spec, such as: xxx.svg.
• pdf_caption — probability density image caption
• cdf_image — cumulative distribution image-spec, such as: yyy.svg.
• cdf_caption — cumulative distribution image caption
• notation — typical designation for this distribution, for example ${\mathcal {N}}(\mu ,\sigma ^{2})$ . The notation should include all the distribution parameters explained in the next cell.
• parameters — parameters of the distribution family (such as μ and σ2 for the normal distribution).
• support — the support of the distribution, which may depend on the parameters. Specify this as $x \in some set$ for continuous distributions, and as $k \in some set$ for discrete distributions.
• pdf — probability density function (or probability mass function), such as: $\frac{\Gamma(r+k)}{k!\,\Gamma(r)}\,p^r\,(1-p)^k \!$. Please exclude the function label, such as “ƒ(x; μ,σ2)”.
• cdf — cumulative distribution function, e.g.: $I_p(r,k+1)\text{ where }I_p(x,y)$ is the [[regularized incomplete beta function]].
• quantilequantile function (or inverse cumulative distribution function). If $F()$ is the CDF and $Q()$ is the quantile function, then $Q(F(x))=x$ • mean — the mean, or expected value.
• median — the median, only for univariate distributions.
• mode — the mode.
• variancevariance of the distribution, or covariance matrix in multivariate case.
• skewness — the skewness.
• kurtosis — the kurtosis excess.
• entropy — the differential information entropy, preferably expressed in unspecified units using base-unspecific log(.) rather than base-specific ln(.) which yields entropy in units of nats only.
• mgf — the moment-generating function, for example: $\left(\frac{p}{1-(1-p) e^t}\right)^r \!$.
• char or cf — the characteristic function, such as: $\left(\frac{p}{1-(1-p) e^{i\,t}}\right)^r \!$.
• pgf - the Probability-generating function.
• fisher — the Fisher information matrix for the model.
• intro — optional message which will be displayed before all other content in the infobox.
• marginleft — margin space left of infobox (default: 1em).
• box_width — width of the infobox (default: 325px).